Scientific Results

  • ID:
    publications-4879
  • Type:
    Conference paper
  • Year:
    2024
  • Authors:
    Lee A.; King K.; GraΔ_x008d_anin D.; Azab M.
  • Title:
    Experiential Learning Through Immersive XR: Cybersecurity Education forÎ’ Critical Infrastructures
  • Venue/Journal:
    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
  • DOI:
    10.1007/978-3-031-61382-1_4
  • Research type:
  • Water System:
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  • Abstract:
    In our modern digital world, where virtually everything is intertwined with computer systems, critical infrastructures face vulnerability to a variety of cyber-attacks, stemming from the absence of a cybersecurity mindset within these establishments. We need to efficiently educate these workers about the cybersecurity threats that exist, their potential effects, and the subsequent substantial impact on human populations. Previous research has suggested traditional non-interactive training methods are often not effective. We propose an interactive learning experience that incorporates Extended Reality, Digital Twins, and Artificial Intelligence (AI) to help workers become more aware of cybersecurity issues within their critical infrastructure. This paper introduces an innovative testbed that seamlessly integrates Artificial Intelligence (AI) and Large Language Models to create an immersive educational experience. The goal is to effectively convey complex technical concepts to users with limited background knowledge on the subject. Our specific focus lies in addressing the need for proper cybersecurity training among water treatment plant employees. The testbed presented is meticulously crafted to provide users with a tangible representation of the potential outcomes resulting from successful cyber attacks on such facilities. Through this approach, we aim to enhance the educational process and promote a deeper understanding of cybersecurity challenges in critical infrastructure like water treatment plants. Β© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
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